The present invention is related to, and claims priority from, Japanese Patent Application No. Hei. 11-28806 filed on Feb. 5, 1999, the contents of which are incorporated herein by reference.
1. Field of the Invention
The present invention relates to air-conditioning systems and, more particularly, to an apparatus for calculating a controlled variable, such as airflow (blower speed), based on n detected variables including outside (ambient) air temperature, interior (cabin) temperature, and amount of sunlight (sun load).
2. Description of the Related Art
A conventional automated climate control (ACC) system typically controls airflow, air temperature at the air distribution ductr exit, or other variables according to environmental conditions such as outside air temperature, interior temperature, and amount of sunlight. Control characteristics for calculating a controlled variable, such as airflow or the temperature at the air distribution duct exit (outlet temperature), from environmental conditions are typically adjusted for each vehicle and stored in a non-volatile system memory such as a ROM, and therefore are usually impossible to modify once they are stored.
Systems utilizing such control characteristics have certain limitations. For example, to control airflow in a system in which the control characteristics are unalterable, sensors that detect outside air temperature, interior temperature, and amount of sunlight generate signals representative of the measured amounts. The airflow is calculated based on these three input signals according to the aforementioned control characteristics, and operation of a blower is controlled to achieve the calculated airflow.
FIG. 15 is a cooling airflow control characteristic map showing one example of control characteristics used to calculate airflow. In this case, the outside air temperature and the amount of sunlight are regarded as constant. Only the interior temperature is varied.
As the interior temperature approaches the set temperature (25xc2x0 C. in this example), the airflow is minimized. As the interior temperature rises above the set temperature, the airflow is increased. The flow rate is maximized around 50xc2x0 C. Where plural input signals are used, a similar map is typically utilized in calculating the controlled variable based on the control characteristics.
In a conventional control procedure using a map based on plural input signals (assuming that there are two input signals; that is, airflow is calculated from both interior temperature and amount of sunlight), as shown in FIG. 16, airflow corresponds to a point (x, y) on a plane that is determined by the interior temperature (x) and the amount of sunlight (y). However, it is unrealistic to make the airflow correspond to every point (x, y) on the plane that is determined by the interior temperature (x) and the amount of sunlight (y), i.e., the entire input space.
Therefore, as shown in FIG. 16, the input space is divided into subspaces orcells. Each airflow value corresponds to the intersections of lines indicating boundaries between the cells. Airflow corresponding to a point inside a cell is found by bilinear interpolation.
In the example shown in FIG. 16, if two input signals indicating the interior temperature (x) and the amount of sunlight (y), respectively, are entered, a decision is made to determine to what cell a point A(x, y) on a plane determined by the interior temperature (x) and the amount of sunlight (y) belongs. Bilinear interpolation is performed, based on four vertices (x0, y0), (x1, y0), (x0, y1), and (x1, y1) defining the cell and on the stored airflow value corresponding to the four vertices.
If blw00, blw10, blw01, and blw11 represent airflows corresponding to the four vertices (x0, y0), (x1, y0), (x0, y1), and (x1, y1), respectively, the algorithm of this bilinear interpolation is as follows. First, X and Y are calculated using Eqs.(1) and (2).                     X        =                              x            -                          x              0                                                          x              1                        -                          x              0                                                          (        1        )                                Y        =                              y            -                          y              0                                                          y              1                        -                          y              0                                                          (        2        )            
An airflow blw corresponding to the point A(x, y) is calculated using Eq. (3).
blw=(1xe2x88x92X)(1xe2x88x92Y)xc3x97blw00+X(1xe2x88x92Y)blw10+(Xxe2x88x921)Yxc3x97blw01+XYxc3x97blw11xe2x80x83xe2x80x83(3)
It should be noted that, although the above description is based on two input signals, calculations can be performed by a similar procedure if there are three or more input signals.
Generally, preset control characteristics based on the above conventional technique are embodied as relations of the vertices of a subspace in an input space to airflows at the vertices. Since bilinear interpolation is used for calculation of a controlled variable based on the preset control characteristics, the amount of required calculations increases with increasing the number of input signals.
In the above conventional air conditioning system, if a system user is dissatisfied with the automatically controlled airflow, the user must typically manually adjust the airflow through a switch or the like. This manual control can enable the system to store. teacher data that can be utilized to update the preset control characteristics favored by the user.
Use of such teacher data will now be explained based on the following example. Preferred airflows of three panelists (users) N, T, and Y during cooling are illustrated in FIGS. 17A-17C, which show the relation of the interior temperature to preferred airflows of users N, T, and Y where the amount of sunlight is kept at 500 W/m2. FIG. 17A shows the case in which the outside air temperature is 20xc2x0 C. FIG. 17B shows the case in which the outside air temperature is 30xc2x0 C. FIG. 17C shows the case in which the outside air temperature is 35xc2x0 C.
FIG. 18 simplifies the results shown in FIG. 17B. As can be seen, the preferred airflows of panelists (or users) N, T, and Y relative to various interior temperatures appear as a gradient of a cooling airflow control characteristic line from the maximum airflow to the minimum airflow shown in the map of FIG. 15. To realize control favored by each user by the learning of the control characteristics, it is necessary to vary the gradient of the control characteristic map lines. For example, where the airflow is controlled based on the map illustrating the preset control characteristics between the interior temperature and airflow as shown in FIGS. 19A and 19B, if the user reduces the airflow at interior temperature T1 and increases the airflow at interior temperature T2, as shown in FIG. 19A, the map is modified to the form shown in FIG. 19B. That is, a gradient is given to the characteristic line such that it passes through the modified airflows at the interior temperatures T1 and T2 at which the modifications were made.
Japanese Patent Application Laid-Open No. 5-149602 discloses a learning technique for household air-conditioning system control characteristics. This technique modifies the control characteristics only the vicinity of teacher data by adding the difference between the present control and the teacher data, as illustrated in FIG. 20. Therefore, it is impossible to realize control of the airflow in a favorable manner for the user under all environmental conditions.
Japanese Patent Application Laid-Open No. 7-172143 discloses a technique for learning an airflow upper limit at the start of operation of an ACC based on outside air temperature and amount of sunlight. In this disclosed technique, outside air temperature is accepted as an input signal. The graphed mapped control characteristics are used to calculate the airflow upper limit, and are modified according to the single input signal. Although the gradient of the graphed control characteristics are modified, the map is associated with only one input signal. Therefore, with respect to the amount of sunlight, either one of two kinds of maps is used, depending on whether the amount of sunlight is greater or smaller than a threshold.
The above situation is illustrated in FIGS. 21A and 21B. FIG. 21A illustrates a map prior to a learning process. FIG. 21B illustrates a map after the learning process. A map consisting of graphed lines indicating control characteristics used to calculate a controlled variable (airflow upper limit) from the outside air temperature is used. Although the gradient of the control characteristic line can be changed, only two control characteristic lines are used, depending on whether the amount of sunlight is large or small.
Accordingly, it is impossible to provide continuous control in response to the amount of sunlight. Hence, fine control cannot be provided in response to the amount of sunlight. Where the number of input signals is increased, if this method is still used, the number of control characteristic lines to be stored in memory correspondingly increases. For example, where two control characteristics are used, such as radiator water temperature and amount of sunlight, a control characteristic line is necessary under conditions where the amount sunlight is large and the radiator water temperature is high, while another control characteristic line is necessary under conditions where the amount of sunlight is large and the radiator water temperature is low. Also, a control characteristic line is necessary under conditions where the amount of sunlight is small and the radiator water temperature is high, while another control characteristic line is necessary under conditions where the amount of sunlight is small and the radiator water temperature is low. Thus, four control characteristic lines are needed.
As shown in FIG. 2A, control characteristics for calculating one controlled variable from two input signals are generally represented as a surface that is a two-dimensional figure embedded in a three-dimensional space. Ideally, the position and curvature at each portion on the surface are updated according to teacher data. However, updating such an arbitrary surface is difficult from a technical standpoint.
In view of the above limitations, it is an object of the present invention to provide an apparatus for controlling a controlled variable based on one or more input variables. It is also an object of the invention to provide a controlled variable-calculating apparatus that can learn control characteristics for calculating a controlled variable.
Specifically, the present invention provides a variable-calculating apparatus that calculates a controlled variable in response to n input variables, where n is a natural number. The variable-calculating apparatus is equipped with a storage device for storing equations for flat planes that make it possible to calculate an output number from n input variables.
The stored equations are defined corresponding to subspaces obtained by dividing an n-dimensional input space having an assemblage of points within an n-dimensional space corresponding to n input variables. The n input variables can be expressed as a point within the n-dimensional input space. Therefore, an assemblage of points corresponding to the n variables forms a region within then-dimensional space according to the range of values that each variable can assume. This region is herein referred to as the n-dimensional input space. For example, where n is 3, the region takes the form of a parallelepiped. If n is 2, it is a region in the form of a rectangle.
The aforementioned equations for flat planes are defined corresponding to these subspaces, respectively. If n input variables are entered, the controlled variable-calculating apparatus. selects an equation for a flat plane stored corresponding to a subspace to which the input variables belong. Using the selected equation, one controlled variable is calculated.
In order to calculate the controlled variable from n input variables, it is necessary to map an n-dimensional input space onto a one-dimensional space. For example, as shown in FIG. 2A, mapping from a two-dimensional input space onto a one-dimensional space can be defined using a surface that is a smooth two-dimensional figure embedded in a three-dimensional space, as shown in FIG. 2A. In FIG. 2A, if the amount of sunlight and the interior temperature are determined, i.e., if a point within a flat plane defined by two values (i.e., the amount of sunlight and the interior temperature) taken on two axes is set, the airflow is computed by finding the point intersecting the surface. By extending this theory, mapping from the n-dimensional space onto the one-dimensional space can be defined using the surface embedded in the (n+1)-dimensional space.
The surface has the same nature as a flat plane when viewed closely to each point (xe2x80x9cModern Small Mathematical Encyclopediaxe2x80x9d, p. 356, 1977, Kodan-sha Bluebacks Publishing Company, Japan). This nature also holds irrespective of the dimensional space in which the surface is embedded. Accordingly, an arbitrary surface can be approximated by combining sufficiently small flat planes by making use of the relation described above. Therefore, the control characteristics represented by the surface as described above can be approximated by combining sufficiently small flat planes.
In view of this fact, the present invention utilizes an n-dimensional input space divided into subspaces, with equations for flat planes being formulated to correspond to the subspaces, respectively. The input space may also be divided into cells, and the planes made to correspond to the cells, respectively. Because it is necessary to divide the whole space into numerous cells for approximation accuracy purposes, the possibility that the number of planes is increased wastefully is high. Accordingly, in the present invention, subspaces corresponding to the input variables are specified. The controlled variable is calculated using equations for flat planes corresponding to these subspaces.
In the controlled variable-calculating apparatus of the present invention, equations for flat planes corresponding to subspaces for n input variables are selected. Using the selected equation for flat planes, the controlled variable is calculated. Generally, an equation for a flat plane is given by
f(x)=ax+by+ . . . +cz+d
Such an equation can be quickly calculated from the n input variables x, y, . . . , z. Consequently, the controlled variable can be easily calculated.
In addition, the apparatus of the present invention includes a controlled variable modifier for modifying the controlled variable from the outside, as well as a learning control device. When the controlled variable is modified via the controlled variable modifier, the learning control device stores the modified controlled variable and input variables entered on this modification as teacher data in a teacher data storage device. The data is stored as teacher data corresponding to subject subspaces corresponding to the input variables. The learning control device updates the equation for a flat plane corresponding to the subject subspace based on the teacher data corresponding to the corresponding subspaces, with the teacher data being included in the teacher data stored in the teacher data storage device.